Spectral imaging is based on capturing multiple channels of color data for each pixel in an image. Each channel is associated with a different spectral sensitivity signature. Spectral imaging with its multiple channels is distinguished from traditional imaging because the latter typically collects only three channels, usually red, green and blue. A properly calibrated spectral approach can maintain the reflectance or transmittance properties of scene objects or can detect the energy level of quanta which reach the detector for each pixel. Traditional imaging systems can not do this and are limited to describing color appearance of a scene under highly constrained environmental conditions. Thus, spectral imaging far exceeds traditional imaging in terms of flexibility, power and the ability to analyze scene contents.
Since spectral imaging systems are based on capturing multiple channels of color data, they capture and require the processing and storage of far more data than traditional imaging systems. As a result, spectral imaging systems are faced with data overload problems.